Firm Growth and Technical Efficiency in Ethiopia: The Role of Firm Size and Finance
Bibliographic record
Abstract
<p>The performance of manufacturing firms can play a crucial rule in spurring economic growth and international competency. However, it has received little attention in developing countries particularly in Sub-Saharan Africa (SSA). Using firm level data from 2000 to 2008 survey, this paper empirically investigates the key determinants of growth and technical efficiency of Ethiopian manufacturing establishments focusing on the impact of size and finance. The empirical result using dynamic panel data estimation suggest that small and young firms grow more rapidly. Leverage ratio and cash flow are also main determinants of firm growth. However, they have heterogeneous effect. While, the availability of internal finance significantly affect the growth of smaller firms, leverage (borrowing) represent a binding constraint for growth of large firms. Firm’s asset, labour quality, ownership and legal status are also binding constraints for growth of firm in Ethiopia. Moreover, a stochastic frontier analysis of the production function shows that there is significant difference in efficiency scores across firms. The result shows that efficiency score increases with firm size and cash flow but decrease with borrowing.</p><p> </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".